Research on the Homogenization of Network Information Based on Chinese Social Media Weibo and Zhihu

Abstract: This study investigates the phenomenon of information homogenization on Chinese social media platforms, specifically focusing on Weibo and Zhihu. As two of Chinas largest and most influential platforms, they provide contrasting environmentsWeibo for mass, entertainment-driven content, and Zhihu for in-depth knowledge discussing and sharing. By analyzing data from both platforms between July 2022 and April 2024 using natural language processing and Latent Dirichlet Allocation (LDA) models, this research reveals that information homogenization has increased on Zhihu, driven by concentrated discussions around a few trending topics, and the corresponding push strategies of online platforms. In contrast, Weibo has maintained a relatively stable, high degree of homogenization throughout the period. These trends highlight the growing challenge of content diversity on Chinese social networks, posing implications for both users and platforms. The findings underscore the need for strategies that balance user engagement with the promotion of diverse content, contributing to a healthier online ecosystem and better information consumption.

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Publication Details

Journal
Communications in Humanities Research
Published
2024-11-15
DOI
https://doi.org/10.54254/2753-7064/42/20242501
Primary Topic
Regional Development and Environment
Type
article
Field-Weighted Citation Impact
0.00
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Research on the Homogenization of Network Information Based on Chinese Social Media Weibo and Zhihu

Mengmeng Gu
Communications in Humanities Research
Regional Development and Environment
article

Research on the Homogenization of Network Information Based on Chinese Social Media Weibo and Zhihu

Mengmeng Gu
article en

Abstract

Abstract: This study investigates the phenomenon of information homogenization on Chinese social media platforms, specifically focusing on Weibo and Zhihu. As two of Chinas largest and most influential platforms, they provide contrasting environmentsWeibo for mass, entertainment-driven content, and Zhihu for in-depth knowledge discussing and sharing. By analyzing data from both platforms between July 2022 and April 2024 using natural language processing and Latent Dirichlet Allocation (LDA) models, this research reveals that information homogenization has increased on Zhihu, driven by concentrated discussions around a few trending topics, and the corresponding push strategies of online platforms. In contrast, Weibo has maintained a relatively stable, high degree of homogenization throughout the period. These trends highlight the growing challenge of content diversity on Chinese social networks, posing implications for both users and platforms. The findings underscore the need for strategies that balance user engagement with the promotion of diverse content, contributing to a healthier online ecosystem and better information consumption.

Communications in Humanities ResearchVol. 42(1)
Wuhan University (CN)
Openalex Percentile: Top 67%
Regional Development and Environment
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